For many types of processes, queuing theory is used in modeling the performance of systems based on quantities such as, but not limited to, expected or anticipated arrival rates of service requests and server processing performance rates. In general, the items moving through a queuing system are referred to in different contexts as customers in the case of queues at fast food restaurants and supermarkets, as calls in the case of circuit-switched telephone switching and trunking networks, as packets in the case of packet networks, and as jobs or processes in the case of programs running on computer processors. In queuing theory models, generally the entities that process service requests are called servers, regardless of whether the server is a person or a processor in a machine. More complicated queuing systems can be made up of networks of queues.
With the advent of various digital technologies, many types of service requests communicated over telecommunication facilities have been automated. For instance, Internet search engines have simplified some look-up tasks. As another non-limiting example, telephone requests for bank balances may now be handled using integrated voice response (IVRs) or voice response units (VRUs) that generally process dual-tone multi-frequency (DTMF) or touch tone recognition systems that allow customers to enter account numbers and passwords. In addition, more sophisticated signal processing techniques now might use voice or speech recognition technology to interpret a customer's request for service that is transmitted over a telephone call. Queuing theory may be used in properly sizing the equipment needed to meet these service requests of customers based on expected probability distributions and timing of customer requests. From an economic standpoint, it is important to provide reasonable customer service using such systems while using the minimum amount of expensive hardware. Here queuing theory helps to determine the amount of equipment needed to meet performance objectives.
Despite the amazing capabilities of digital equipment, some tasks are still best performed by humans. For instance, even with the amazing improvements in speech recognition, humans are still much better at interpreting verbal messages from another human even when the verbal messages are communicated over telecommunication facilities. Also, although some Internet search engines over natural language format searches, the ability of computers to interpret grammar, semantics, and context for natural human language is still quite limited. Thus, human beings may still be better at processing natural language requests even though the requests may be typed into a computer.
While queuing theory is useful in properly sizing the equipment needed for processing some service requests, such as but not limited to Boolean Internet searches, VRU requests, and voice recognition requests, which are communicated over telecommunication facilities, queuing theory may also be used in properly sizing the number of human beings needed to handle service requests that cannot be easily dealt with using digital technology. One common non-limiting example of service requests that might be handled by human service agents is an inbound call center that handles telephone orders for sporting event tickets or goods. Other common non-limiting examples are directory assistance and operator services of a telephone company. In addition, the 911 emergency phone number generally is directed to an inbound call center. While many inbound call centers process human voice communications to interpret and respond to a customer's service request, some call centers also offer the ability to communicate with handicapped customers who may be deaf and/or mute, and may use special terminals to type in natural language queries of request for service. These natural language service requests may still be processed by human service agents or human servers as opposed to digital machines. Thus, human service agents handle more types of service requests, which are transmitted over telecommunication facilities, than are just communicated over the telecommunication facilities as voice signals of human language.
Generally, service centers using telecommunications facilities may be categorized as inbound and/or outbound centers. In the case of call centers handling telephone calls, outbound centers typically generate outbound phone calls for applications such as, but not limited to, telemarketing, charitable donation solicitation, and survey completion solicitation. Inbound call centers generally handle inbound phone calls that may be processed using equipment such as an Automated Call Distributor (ACD) that directs calls to an available server (human or machine) to properly handle customer service requests. Also, a particular call center may perform both inbound and outbound activities such that the categories of inbound and outbound are not mutually exclusive.
Staffing a service center with the proper number of human service agents to efficiently handle the volume or load of incoming service requests, which are transmitted over telecommunication facilities, is an important business and technical problem. On the one hand, it is expensive to overstaff a service center with too many human service agents that will be underutilized. Also, understaffing a service center with too few human service agents could lead to poor customer service and possibly loss of sales revenue. Workforce management systems or force management systems (FMSes) have been developed to help managers with the resource planning of staffing a service center. However, these FMS systems usually are not fully integrated with the ACD or other service request distribution equipment. This lack of integration misses some opportunities to improve the efficiency of systems handling incoming service requests transmitted over telecommunication facilities.
Thus, a heretofore unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies.